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Frederick M Howard

Showing results (41-50 of 54) with videos related to

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Biorxiv : the Preprint Server for Biology|April 8, 2024
Generative Adversarial Networks Accurately Reconstruct Pan-Cancer Histology from Pathologic, Genomic, and Radiographic Latent FeaturesFrederick M Howard, Hanna M Hieromnimon, Siddhi Ramesh, et al.
Science Advances|November 15, 2024
Generative adversarial networks accurately reconstruct pan-cancer histology from pathologic, genomic, and radiographic latent featuresFrederick M Howard, Hanna M Hieromnimon, Siddhi Ramesh, et al.
Medrxiv : the Preprint Server for Health Sciences|July 15, 2025
Deep Learning on Histopathological Images to Predict Breast Cancer Recurrence Risk and Chemotherapy BenefitGil Shamai, Shachar Cohen, Yoav Binenbaum, et al.
The Lancet. Oncology|March 14, 2026
Deep learning on histopathological images to predict breast cancer recurrence risk and chemotherapy benefit: a multicentre, model development and validation studyGil Shamai, Shachar Cohen, Yoav Binenbaum, et al.
Radiology. Artificial Intelligence|December 11, 2023
External Evaluation of a Mammography-based Deep Learning Model for Predicting Breast Cancer in an Ethnically Diverse PopulationOlasubomi J Omoleye, Anna E Woodard, Frederick M Howard, et al.
Genome Medicine|August 8, 2025
Building digital histology models of transcriptional tumor programs with generative deep learning for pathology-based precision medicineHanna M Hieromnimon, James Dolezal, Kristina Doytcheva, et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|November 10, 2025
Machine Learning-Based Prediction of Distant Recurrence Risk and Ribociclib Treatment Effect in HR+/HER2- Early Breast Cancer Using Real-World and NATALEE DataFrederick M Howard, Peter A Fasching, Cesar A Santa-Maria, et al.
Breast Cancer Research : BCR|May 25, 2023
Molecular profiling of a real-world breast cancer cohort with genetically inferred ancestries reveals actionable tumor biology differences between European ancestry and African ancestry patient populationsMinoru Miyashita, Joshua S K Bell, Stephane Wenric, et al.
NPJ Precision Oncology|May 29, 2023
Deep learning generates synthetic cancer histology for explainability and educationJames M Dolezal, Rachelle Wolk, Hanna M Hieromnimon, et al.
Oral Oncology|March 5, 2025
Analysis of AI foundation model features decodes the histopathologic landscape of HPV-positive head and neck squamous cell carcinomasHanna M Hieromnimon, Anna Trzcinska, Frank T Wen, et al.
Pageof 6

Showing results (41-50 of 54) with videos related to

Sort By:
Pageof 6
Biorxiv : the Preprint Server for Biology|April 8, 2024
Generative Adversarial Networks Accurately Reconstruct Pan-Cancer Histology from Pathologic, Genomic, and Radiographic Latent FeaturesFrederick M Howard, Hanna M Hieromnimon, Siddhi Ramesh, et al.
Science Advances|November 15, 2024
Generative adversarial networks accurately reconstruct pan-cancer histology from pathologic, genomic, and radiographic latent featuresFrederick M Howard, Hanna M Hieromnimon, Siddhi Ramesh, et al.
Medrxiv : the Preprint Server for Health Sciences|July 15, 2025
Deep Learning on Histopathological Images to Predict Breast Cancer Recurrence Risk and Chemotherapy BenefitGil Shamai, Shachar Cohen, Yoav Binenbaum, et al.
The Lancet. Oncology|March 14, 2026
Deep learning on histopathological images to predict breast cancer recurrence risk and chemotherapy benefit: a multicentre, model development and validation studyGil Shamai, Shachar Cohen, Yoav Binenbaum, et al.
Radiology. Artificial Intelligence|December 11, 2023
External Evaluation of a Mammography-based Deep Learning Model for Predicting Breast Cancer in an Ethnically Diverse PopulationOlasubomi J Omoleye, Anna E Woodard, Frederick M Howard, et al.
Genome Medicine|August 8, 2025
Building digital histology models of transcriptional tumor programs with generative deep learning for pathology-based precision medicineHanna M Hieromnimon, James Dolezal, Kristina Doytcheva, et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|November 10, 2025
Machine Learning-Based Prediction of Distant Recurrence Risk and Ribociclib Treatment Effect in HR+/HER2- Early Breast Cancer Using Real-World and NATALEE DataFrederick M Howard, Peter A Fasching, Cesar A Santa-Maria, et al.
Breast Cancer Research : BCR|May 25, 2023
Molecular profiling of a real-world breast cancer cohort with genetically inferred ancestries reveals actionable tumor biology differences between European ancestry and African ancestry patient populationsMinoru Miyashita, Joshua S K Bell, Stephane Wenric, et al.
NPJ Precision Oncology|May 29, 2023
Deep learning generates synthetic cancer histology for explainability and educationJames M Dolezal, Rachelle Wolk, Hanna M Hieromnimon, et al.
Oral Oncology|March 5, 2025
Analysis of AI foundation model features decodes the histopathologic landscape of HPV-positive head and neck squamous cell carcinomasHanna M Hieromnimon, Anna Trzcinska, Frank T Wen, et al.
Pageof 6